J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (5): 660-670.doi: 10.1007/s12204-022-2450-5

• Automation System & Theory • Previous Articles     Next Articles

Target Detection Algorithm Based On Human Judge Mechanism

SHI Jichao1 (石继超), WANG Ziheng2 (王子恒), ZHAO Xianchao1 (赵现朝), ZHANG Zhinan1∗ (张执南)   

  1. (1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Whiting School of Engineering, Johns Hopkins University, Baltimore MD 21218, USA)
  • Received:2021-01-25 Online:2022-09-28 Published:2022-09-03

Abstract: A D-G-YOLOV3 algorithm was proposed to identify and judge recyclables, which introduced a dense feature network to replace the feature pyramid network. The network closely connects and fits the feature maps and simulates human judgment mechanism. A three-stage judgment is made for judgment objects with lower confidence. Based on the judgment of the original image, the second-stage judgment is carried out after the channel contrast is increased. Finally, sampling is performed on the region of interest where the second-stage confidence score wins for the third stage of judgment, and then judgment result is sent to the gated recurrent unit network for final inference. The result shows that through experiments on the same recyclables data set, the algorithm reduces the missed detection rate by 15.54%, and the false detection rate by 0.97%, while improves the accuracy rate by 16.51%.

Key words: target detection, dense feature network, human judge mechanism, recyclable

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